In recent years, virtual assistants have become a central asset for technological companies.
This has increased the interest of AI researchers in studying and developing conversational agents, some popular examples being Google Home, Siri and Alexa. This has renewed the research interest in Question Answering (QA) and, in particular, in two main tasks: (i) answer sentence selection (AS2), which, given a question and a set of answer sentence candidates, consists in selecting sentences (e.g., retrieved by a search engine) correctly answering the question; and (ii) machine reading (MR) [1]} or reading comprehension, which, given a question and a reference text, consists in finding a text span answering it. Even though the latter is gaining more and more popularity, AS2 is more relevant to a production scenario since, a combination of a search engine and an AS2 model already implements an initial QA system.
